The use of autonomous mobile sensing platforms (i.e., robotic vehicles) is desirable in many applications because of hostile environments, inherently dangerous tasks and/or cost considerations. For example, the military's searching for land mines buried in the ground or under the seafloor is ideally carried out without the use of any personnel in the searching vicinity. In the commercial world, robotic vehicles can be used to locate and track buried cables and/or pipelines. In each of these uses, the “target” generally is made at least partially from a magnetically polarizable material.
U.S. Pat. No. 6,476,610 discloses a magnetic anomaly sensing system and method that derives target localization signals from mathematical scalar contractions of the magnetic gradient tensor (i.e., rate of change of the magnetic field relative to an X,Y,Z component distance between two sensing locations). The gradient contraction scalar methods for scalar-based triangulation and ranging use square and cubic arrays of triaxial magnetometers to effectively develop more than five gradient components at each point of the sensor system's space. While this approach provides a robust method of target localization, it may also be too complex for simple guidance. This approach's complexity highlights some shortcomings that can hinder its effectiveness if used as the basis for a magnetic guidance system. More specifically, if a vehicle must be guided to contact or near contact with the magnetic target, errors in target localization can result because the approach relies on i) the use of the far-field dipole approximation for the target's magnetic signature, ii) the assumption that the distance from the sensing vehicle to the target is much greater than the distance between sensing locations on the vehicle, and iii) solutions of inverse trigonometric functions which can cause errors for certain vehicle angles of approach to the target.